About

Predictive models and analysis are typically used to forecast future probabilities. Applied to business, predictive models are used to analyze current data and historical facts in order to better understand customers, products and partners and to identify potential risks and opportunities for a company. Predictive Risk Analytics (PRA) uses a number of techniques, including data mining, statistical modeling and machine learning to help analysts make future business forecasts.” However, our RuleSphere research over the course of 2013 and 2014 has indicated that the current PRA vendors do not address the areas of enterprise resiliency and complexity management. For this reason, RuleSphere has entered this market with the help of our partner Ontonix S.r.l.

Current vendors in the Predictive Risk Analytics software application marketplace include the following vendors. But once you explore them, you will quickly find out that none of the vendors, except Ontonix / RuleSphere address enterprise resiliency, complexity management, critical infrastructure and our other application-focused solution areas shown on our home page:

• Angoss

• IBM Predictive Analytics

• KXEN

• Ontonix / RuleSphere International, Inc. < Leadership in Quantive Complexity Management, critical infrastructure oversight, internal audit programs for complexity management

• Oracle Data Mining

• Palantir

 Pervasive

• Revolution Analytics

• Salford Systems

• SAP Predictive Analytics

• SAS Analytics

• Statistica

• Tibco Analytics Software

Ontonix provides a new Predictive Risk Analytics approach with a highly differentiated SaaS-based multi-tenant application. Ontonix and RuleSphere focus on helping companies to assess the mission-critical areas of enterprise infrastructure and resilience. Ontonix solutions are now available to customers in North America through RuleSphere.


About

RuleSphere helps companies to build enterprise agility through Predictive Risk Analytics. We do this by helping our clients to reduce the cycle-time needed to respond to business change. We help our customers to achieve breakthrough performance using progressive business systems and infrastructure that foster unparalleled agility and flexibility in business operations and information systems. 


Why is a Predictive Risk Analytics Initiative so important in driving strategic shareholder value?

1.) Improve critical thinking

2.) Foster a new understanding of how to enhance an individual’s abilities in complex problem solving, and 

3.) Strengthen judgment and decision-making 

These 3 Critical Success Factors, in turn, drive and enhance four other enterprise capabilities...

4.) Corporate Architectures of the Future 

5.) Organizational Performance

6.) Operational Effectiveness

7.) "Concurrent Enterprising" including the development of parallel ways of working, and collaborative work methods


RuleSphere associates and alliance partners are thought-leaders, designers, implementers, and practitioners in building progressive business systems that drive business transformation. We guide dramatic business transformations through broad human, business, and technical system integration experience, know-how, and skills. Our industry solutions transform your enterprise into a leading-edge business operation. This transformation unlocks the inherent abilities of your company in becoming responsive to business change and radically reducing the cycle-time associated with it!

 

Contact:

RuleSphere International, Inc.

P.O. Box 152

Still River, MA 01467-0152

USA


Telephone: (978)456-8253
 

E-Mail: info (at) rulesphere (dot) com

 

What is Complexity Management?

Dr. Jacek Marczyk of Ontonix S.r.l. in Como, Italy contends that "a widely accepted definition of complexity does not really exist. Many of the popular definitions refer to complexity as a 'twilight zone between chaos and order'.  A belief is often held that in this twilight zone natural organisms not only exist, but they are most prolific. Within this region life can be created and sustained." Others claim that the phenomena of self-emergence or spontaneous self-organization are manifestations of complexity. Dr. Marczkk adds, "clearly, such definitions do not lend themselves to any practical use since they don´t suggest any measure or quantity. In fact, contemporary "complexity science" has been unable to provide a metric of complexity. At Ontonix, we have developed the first commercially available Predictive Risk Analytic (PRA) software application that is the incarnation of the Quantitative Complexity Theory (QCT). We define complexity as function of structure and entropy (uncertainty). Complexity, according to our approach, is not a phenomenon, it is a property of every system, just like energy, or potential. Formally, we can say that C=f(S; E), where S represents the structure of a system while E stands for entropy. Humans instinctively try to avoid highly complex scenarios because of one fundamental reason - high complexity has a major downside. This is the negative ability to deliver surprising behavior when it is least expected. However, at the same time, higher complexity often means more functionality. This is why, for example, in the natural evolution of species, each organizm strives to attain higher complexity as a means of increasing survivability.

 

FURTHER READING:

Battram, Arthur. Navigating Complexity: The Essential Guide to Complexity Theory in Business and Management. London: Spiro Press, 2002.

Caldart, Adrián A., and Joan E. Ricart. "Corporate Strategy Revisited: A View from Complexity Theory." European Management Review 1, no. 1 (2004): 96–104.

Casti, John L. Complexification: Explaining a Paradoxical World Through the Science of Surprise. New York: HarperCollins, 1994.

Hout, Thomas M. "Books in Review: Are Managers Obsolete?" Harvard Business Review 77, no. 2 (1999): 161–168.

Okes, Duke. "Complexity Theory Simplifies Choices." Quality Progress 36, no. 7 (2003): 35–38.

Olsen, Edwin E., Glenda H. Eoyang, Richard Beckhard, and Peter Vaill. Facilitating Organization Change: Lessons from Complexity Science. San Francisco: Pfeiffer, 2001.

Sherman, Howard J., and Ralph Schultz. Open Boundaries: Creating Business Innovation Through Complexity. Reading, MA: Perseus Books, 1998.